Logan Crew, Evan Haithcock, Josephine Reynes, Sophie Spirkl
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We demonstrate that this new function retains the basic properties and basis expansions of <em>X</em>, and we give a method for systematically deriving new linear relationships for <em>X</em> from previous ones by passing them through <span><math><msub><mrow><mi>X</mi></mrow><mrow><mi>k</mi></mrow></msub></math></span>.</p><p>In particular, we show how to take advantage of homogeneous sets of <em>G</em> (those <span><math><mi>S</mi><mo>⊆</mo><mi>V</mi><mo>(</mo><mi>G</mi><mo>)</mo></math></span> such that each vertex of <span><math><mi>V</mi><mo>(</mo><mi>G</mi><mo>)</mo><mo>﹨</mo><mi>S</mi></math></span> is either adjacent to all of <em>S</em> or is nonadjacent to all of <em>S</em>) to relate the chromatic symmetric function of <em>G</em> to those of simpler graphs. 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引用次数: 0
摘要
在本文中,我们将色度对称函数 X 扩展为色度 k 多对称函数 Xk,该函数定义用于将顶点集分割为 k 部分的图。我们证明了这个新函数保留了 X 的基本性质和基扩展,并给出了一种方法,通过 Xk,从以前的函数系统地推导出 X 的新线性关系。特别是,我们展示了如何利用 G 的同质集(那些 S⊆V(G),使得 V(G)﹨S 的每个顶点要么与 S 的所有顶点相邻,要么与 S 的所有顶点不相邻),将 G 的色度对称函数与更简单图的色度对称函数联系起来。此外,我们还展示了如何将这一想法扩展到同质对 S1⊔S2⊆V(G),从而推广 Guay-Paquet 用于将斯坦利-斯坦桥猜想简化为单位区间图的过程。
Homogeneous sets in graphs and a chromatic multisymmetric function
In this paper, we extend the chromatic symmetric function X to a chromatic k-multisymmetric function , defined for graphs equipped with a partition of their vertex set into k parts. We demonstrate that this new function retains the basic properties and basis expansions of X, and we give a method for systematically deriving new linear relationships for X from previous ones by passing them through .
In particular, we show how to take advantage of homogeneous sets of G (those such that each vertex of is either adjacent to all of S or is nonadjacent to all of S) to relate the chromatic symmetric function of G to those of simpler graphs. Furthermore, we show how extending this idea to homogeneous pairs generalizes the process used by Guay-Paquet to reduce the Stanley-Stembridge conjecture to unit interval graphs.
期刊介绍:
Interdisciplinary in its coverage, Advances in Applied Mathematics is dedicated to the publication of original and survey articles on rigorous methods and results in applied mathematics. The journal features articles on discrete mathematics, discrete probability theory, theoretical statistics, mathematical biology and bioinformatics, applied commutative algebra and algebraic geometry, convexity theory, experimental mathematics, theoretical computer science, and other areas.
Emphasizing papers that represent a substantial mathematical advance in their field, the journal is an excellent source of current information for mathematicians, computer scientists, applied mathematicians, physicists, statisticians, and biologists. Over the past ten years, Advances in Applied Mathematics has published research papers written by many of the foremost mathematicians of our time.